Crypto market analysis
Put company announcements, public statements, and changing mentions beside your market data.
Used Perception integration, used a tool
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Perception narrative momentumResult
Perception search mentionsResult
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Claude is AI and can make mistakes. Please double-check responses.
Illustrative chat. Saved research · 27 Sep 2026
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Investigate the context around a market event
A change in price can prompt useful questions about announcements, regulation, or company activity. Perception helps you inspect the mentions around that event and compare it with earlier periods.
A sourced timeline shows what was published and when. Establishing a cause for a market move requires further evidence.
Build a sourced account of the event
Search the company or topic over a defined window. Compare which outlets covered it and how they described it.
Follow related narratives, company mentions, and public statements to identify what deserves a closer read. Keep publication dates and source links in the resulting brief.
What you can track
- Market sentiment trends: Overall sentiment across all sources, broken down by time period. Spot shifts from bullish to bearish the day they start.
- Company mentions: Mention volume, sentiment, and outlet distribution for 110+ tracked entities. Compare companies side by side.
- Narrative momentum: Is "Bitcoin treasury strategy" accelerating or fading? Track any narrative with a -100 to +100 momentum score that quantifies whether mentions are growing or shrinking.
- Analyst consensus: Wall Street price targets, upgrades, and downgrades for 70+ publicly-traded crypto stocks. See where the Street disagrees with the market.
- Regulatory developments: Track SEC enforcement actions, congressional hearings, central bank publications, and policy shifts. Filtered by agency and jurisdiction.
- Fear and Greed Index: The Bitcoin Fear & Greed Index alongside media sentiment for a composite view of market psychology.
Use mentions in your market review
Fund analysts and portfolio managers can investigate changing mentions. When media sentiment on a specific company diverges from analyst consensus, that's a divergence worth investigating. The AI connectors let analysts ask their Claude or ChatGPT setup questions like "What's driving negative sentiment on Marathon this week?" and inspect sourced answers.
Researchers and academics use the historical data to study how media narratives correlate with market movements. The structured sentiment data goes back years, making it useful for quantitative research on information asymmetry in crypto markets.
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